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20202025
most citedExamining Independence in Ensemble Sentiment Analysis: A Study on the Limits of Large Language Models Using the Condorcet Jury Theorem

1 citations · 1 across the 5 of their papers we have counts for

collaborators

8 papers

q-fin.PR2025

Revisiting the Structure of Trend Premia: When Diversification Hides Redundancy

Alban Etienne, Jean-Jacques Ohana, Eric Benhamou +3

Recent work has emphasized the diversification benefits of combining trend signals across multiple horizons, with the medium-term window-typically six months to one year-long viewe…

cs.CL2025

FinMarBa: A Market-Informed Dataset for Financial Sentiment Classification

Baptiste Lefort, Eric Benhamou, Beatrice Guez +3

This paper presents a novel hierarchical framework for portfolio optimization, integrating lightweight Large Language Models (LLMs) with Deep Reinforcement Learning (DRL) to combin…

cs.AI2025

Re-evaluating Short- and Long-Term Trend Factors in CTA Replication: A Bayesian Graphical Approach

Eric Benhamou, Jean-Jacques Ohana, Alban Etienne +3

Commodity Trading Advisors (CTAs) have historically relied on trend-following rules that operate on vastly different horizons from long-term breakouts that capture major directiona…

cs.CL2024★ 1 cited

Examining Independence in Ensemble Sentiment Analysis: A Study on the Limits of Large Language Models Using the Condorcet Jury Theorem

Baptiste Lefort, Eric Benhamou, Jean-Jacques Ohana +3

This paper explores the application of the Condorcet Jury theorem to the domain of sentiment analysis, specifically examining the performance of various large language models (LLMs…

cs.CL2024

Optimizing Performance: How Compact Models Match or Exceed GPT's Classification Capabilities through Fine-Tuning

Baptiste Lefort, Eric Benhamou, Jean-Jacques Ohana +2

In this paper, we demonstrate that non-generative, small-sized models such as FinBERT and FinDRoBERTa, when fine-tuned, can outperform GPT-3.5 and GPT-4 models in zero-shot learnin…

q-fin.ST2024

Stress index strategy enhanced with financial news sentiment analysis for the equity markets

Baptiste Lefort, Eric Benhamou, Jean-Jacques Ohana +3

This paper introduces a new risk-on risk-off strategy for the stock market, which combines a financial stress indicator with a sentiment analysis done by ChatGPT reading and interp…

q-fin.ST2024

Can ChatGPT Compute Trustworthy Sentiment Scores from Bloomberg Market Wraps?

Baptiste Lefort, Eric Benhamou, Jean-Jacques Ohana +3

We used a dataset of daily Bloomberg Financial Market Summaries from 2010 to 2023, reposted on large financial media, to determine how global news headlines may affect stock market…

q-fin.PM2020

Detecting and adapting to crisis pattern with context based Deep Reinforcement Learning

Eric Benhamou, David Saltiel, Jean-Jacques Ohana +1

Deep reinforcement learning (DRL) has reached super human levels in complex tasks like game solving (Go and autonomous driving). However, it remains an open question whether DRL ca…